700+ free, structured notes connecting computer science theory to how it's actually used in industry — from algorithms and operating systems to computer vision, LLMs, and edge AI.
The Computer Science Notebook is an open, community-driven knowledge base that bridges the gap between theoretical computer science and real-world industry applications.
Whether you're a student learning fundamentals, a professional switching domains, or an engineer exploring a new field, this notebook is a practical companion — organized, tiered by skill level, and cross-referenced from theory to practice.
- 📚 700+ notes across AI/ML, programming, systems, engineering, and fundamentals
- 🏭 Industry sections mapping concepts to automotive, aerospace, healthcare, manufacturing, and more
- 🎚️ Tiered content — most topics split into beginner → intermediate → advanced
- 🔎 Searchable docs site built with MkDocs Material — browse it here
| I want to… | Go to |
|---|---|
| Learn AI / Machine Learning | core/ai-ml |
| Master a programming language | core/programming/languages |
| Understand systems & infrastructure | core/systems |
| Level up software engineering | core/engineering |
| See CS applied in industry | industry |
| Prep for technical interviews | meta/career/job-interview-notes |
- Machine Learning · Deep Learning · Computer Vision
- NLP · Generative AI · Prompt Engineering
- AI Agents · Computer Audition · Cognitive Science
- Languages (C, C++, Python, Rust, Go, Java, MATLAB…)
- Algorithms · Data Structures · Design Patterns
- High-Performance Programming · Parallel Programming
- Transportation & Automotive · Aerospace · Healthcare
- Manufacturing · Agriculture · Robotics · Smart City
The notebook is published as a searchable documentation site:
➡️ https://afondiel.github.io/computer-science-notebook/
# Clone the repository
git clone https://github.com/afondiel/computer-science-notebook
cd computer-science-notebook
# Install the docs toolchain
pip install -r requirements-docs.txt
# Serve locally with live reload
mkdocs serveBecause every note is plain Markdown, you can open the whole repository as an Obsidian vault and read, search, and cross-link the notes in a rich linked-knowledge graph — no conversion needed.
See the Authoring Guide for the recommended Obsidian settings (that keep notes MkDocs-compatible) and the AI-assisted note workflow.
Contributions are welcome — add a note, fix a link, improve an explanation, or share an industry case study. Good first contributions are labeled in Issues.
See the Contributing Guide for templates and conventions.
- Content: expand industry coverage, add interactive examples and learning paths
- Platform: searchable docs site (✅ live), improved navigation and tags
- Community: expert contributions, peer review, discussions
Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
If you find this helpful:
- Star the repository ⭐
- Share it with students and colleagues
- Contribute a note or fix
- Report issues or suggest improvements
As a lifelong learner and advocate for accessible education, I hope this project helps you in your journey. Feel free to reach out with questions or suggestions!
Cheers, @Muntu